Brain MR Image Segmentation Based on an Adaptive Combination of Global and Local Fuzzy Energy

This paper presents a novel fuzzy algorithm for segmentation of brain MR images and simultaneous estimation of intensity inhomogeneity. The proposed algorithm defines an objective function including a local fuzzy energy and a global fuzzy energy. Based on the assumption that the local image intensities belonging to each different tissue satisfy Gaussian distributions with different means, we derive the local fuzzy energy by utilizing maximum a posterior probability (MAP) and Bayes rule. The global fuzzy energy is defined by measuring the distance between the original image and the corresponding inhomogeneity-free image. We combine the global fuzzy energy with the local fuzzy energy using an adaptive weight function whose value varies with the local contrast of the image. This combination enables the proposed algorithm to address intensity inhomogeneity and to improve the accuracy of segmentation and its robustness to initialization. Besides, the proposed algorithm incorporates neighborhood spatial information into the membership function to reduce the impact of noise. Experimental results for synthetic and real images validate the desirable performances of the proposed algorithm

Towards Secure Cloud Data Management

This paper explores the security challenges posed by data-intensive applications deployed in cloud environments that span administrative and network domains. We propose a data-centric view of cloud security and discuss data management challenges in the areas of secure distributed data processing, end-to-end query result verification, and cross-user trust policy management. In addition, we describe our current and future efforts to investigate security challenges in cloud data management using the Declarative Secure Distributed Systems (DS2) platform, a declarative infrastructure for specifying, analyzing, and deploying secure information systems

NetTrails: A Declarative Platform for Maintaining and Querying Provenance in Distributed Systems

We demonstrate NetTrails, a declarative platform for maintaining and interactively querying network provenance in a distributed system. Network provenance describes the history and derivations of network state that result from the execution of a distributed protocol. It has broad applicability in the management, diagnosis, and security analysis of networks. Our demonstration shows the use of NetTrails for maintaining and querying network provenance in a variety of distributed settings, ranging from declarative networks to unmodified legacy distributed systems. We conclude our demonstration with a discussion of our ongoing research on enhancing the query language and security guarantees

Distortion of thin-walled structure fabricated by selective laser melting based on assumption of constraining force-induced distortion

Metal additive manufacturing has shown great potential in aerospace, medical, and automobile industries; however, distortion of metal part has been an obstacle in widespread application of metal additive manufacturing. The mechanism of thin-walled structure distortion remains unrevealed. In this study, the origin of distortion of thin-walled structure was discussed, based on the previously proposed assumption of constraining force-induced distortion. The relation between the microstructure and macro-distortion has been linked via the constraining force. The influence of scan directions and structure sizes on the distortion was also studied, and the approaches to decrease the thin-walled structure were discussed. Use of the alternant scan strategy has been validated as an effective approach if the structure sizes cannot be adjusted

Imprint of the stochastic nature of photon emission by electrons on the proton energy spectra in the laser-plasma interaction

The impact of stochasticity effects (SEs) in photon emissions on the proton energy spectra during laser-plasma interaction is theoretically investigated in the quantum radiation-dominated regime, which may facilitate SEs experimental observation. We calculate the photon emissions quantum mechanically and the plasma dynamics semiclassically via two-dimensional particle-in-cell simulations. An ultrarelativistic plasma generated and driven by an ultraintense laser pulse head-on collides with another strong laser pulse, which decelerates the electrons due to radiation-reaction effect and results in a significant compression of the proton energy spectra because of the charge separation force. In the considered regime the SEs are demonstrated in the shift of the mean energy of the protons up to hundreds of MeV. This effect is robust with respect to the laser and target parameters and measurable in soon available strong laser facilities

Detection of sulfur mustard simulants using the microwave atmospheric pressure plasma optical emission spectroscopy method

Sulfur mustard (SM) is one kind of highly toxic chemical warfare agent and easy to spread, while existing detection methods cannot fulfill the requirement of rapid response, good portability, and cost competitiveness at the same time. In this work, the microwave atmospheric pressure plasma optical emission spectroscopy (MW-APP-OES) method, taking the advantage of non-thermal equilibrium, high reactivity, and high purity of MW plasma, is developed to detect three kinds of SM simulants, i.e., 2-chloroethyl ethyl sulfide, dipropyl disulfide, and ethanethiol. Characteristic OES from both atom lines (C I and Cl I) and radical bands (CS, CH, and C2) is identified, confirming MW-APP-OES can preserve more information about target agents without full atomization. Gas flow rate and MW power are optimized to achieve the best analytical results. Good linearity is obtained from the calibration curve for the CS band (linear coefficients R2 > 0.995) over a wide range of concentrations, and a limit of detection down to sub-ppm is achieved with response time on the order of second. With SM simulants as examples, the analytical results in this work indicate that MW-APP-OES is a promising method for real-time and in-site detection of chemical warfare agents

Hormonal therapy is effective and safe for cryptorchidism caused by idiopathic hypogonadotropic hypogonadism in adult males

BackgroundHormonal therapy is a reasonable treatment for cryptorchidism caused by idiopathic hypogonadotropic hypogonadism (IHH). However, the clinical evidence on whether it is effective and safe for the treatment of cryptorchidism caused by IHH is lacking.AimTo evaluate the effect of hormonal therapy in testicular descent, puberty development, and spermatogenesis in adult males with cryptorchidism caused by IHH.MethodsThis retrospective study included 51 patients with cryptorchidism caused by IHH from the Andrology Clinic of University affiliated teaching hospital. Patients were divided into two groups: group A patients received hormonal therapy; group B patients received surgical treatment for cryptorchidism followed by hormonal therapy.ResultsThe rate of successful testicular descent following hormonal therapy (19/32 in group A) or surgical treatment (11/19 in group B) shows no statistically significant difference. There was also no statistically significant difference in penile length, Tanner stage of pubic hair, testicular volume, and success rate of spermatogenesis between the two groups. Testicular atrophy was seen in a single patient in group B.ConclusionsHormone therapy in adult males with cryptorchidism caused by IHH is effective and safe regarding testicular descent, puberty development, and spermatogenesis. This study provides new insight into the treatment of cryptorchidism caused by IHH and highlights that hormonal therapy could be an effective, safe, and economic treatment option for cryptorchidism in males caused by IHH